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贵州省遵义地区3个酱香型大曲细菌群落的比较分析 被引量:24

Comparative Analysis of Bacterial Populations of Three Maotai-Flavored Daqus in Zunyi, Guizhou
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摘要 研究酱香型大曲主要产地遵义地区的细菌类群组成,并利用主成分分析法对这些细菌的类群和大曲的关系进行评定。样品采用454 FLX+平台进行测序,样品中所测微生物为细菌,测序片段为16S r DNA V3~V5区,所有样品的优质序列按97%的相似度进行聚类,计算这些细菌类群的相对含量。用主成分分析法对细菌类群和大曲样品进行分析,结果显示:从3个大曲样品中共检测出6个门49个属细菌,主要是厚壁菌门;样品MT01以高温放线菌属(Thermoactinomyces)34.40%、芽孢杆菌属(Bacillus)31.40%、Scopulibacillus 13.60%为主,占总量的79.40%,样品ZJ01以高温放线菌属(Thermoactinomyces)34.80%、芽孢杆菌属Bacillus 49.00%为主,占总量的84.80%,样品ZX01以高温放线菌属(Thermoactinomyces)66.10%为主;对3个大曲样本进行主成分分析,发现棒状杆菌属(Corynebacterium)、魏斯氏菌属(Weissella)是影响样品MT01与ZJ01距离最近,ZX01相对距离较远的细菌类群。 Bacterial populations of three samples of Maotai-flavored Daqu in Zunyi, Guizhou province were studied. Principal component analysis was used to evaluate the relationship between bacterial population and Daqu. The 454 FLX+ platform was used to sequence the 16 S r DNA gene V3–V5 region of the bacteria. The high quality sequences were clustered by similarity(0.97), and used to calculate the relative content of bacteria. Through principal component analysis, we analyzed the bacterial population of Daqu. Results showed that 6 phyla and 49 genera were detected from three samples, and the Firmicutes were the most dominant phylum. Thermoactinomyce(34.40%), Bacillus(31.40%) and Scopulibacillus(13.60%) were dominant in Daqu MT01, accounting for 79.40% of the total bacterial population. Thermoactinomyce(34.80%) and Bacillus(49.00%) were dominant in Daqu ZJ01, accounting for 84.80%. Only Thermoactinomyce(66.10%) was dominant in Daqu ZX01. Principal component analysis(PCA) suggested that MT01 and ZJ01 were the nearest in distance, and ZX01 was a little far. This study can provide a theoretical basis for the judgment of Daqu quality.
出处 《食品科学》 EI CAS CSCD 北大核心 2016年第7期110-116,共7页 Food Science
基金 科技部科技支撑计划项目(2011BAC06B12) 贵州省科技厅工业攻关项目(黔科合GZ字[2014]3012) 贵州省科技厅重大专项计划项目(黔科合重大专项字[2013]6009号) 贵州省省校合作计划项目(黔科合LH字[2014]7672)
关键词 酱香型大曲 细菌 高通量测序 类群 主成分分析 Maotai-fl avored Daqu bacteria high-throughput sequence population principal component analysis
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